Circular Cross Covariance

Version (1.69 KB) by G. Levin
Circular Cross Covariance function estimate.


Updated 17 Aug 2004

View License

CXCOV Circular Cross Covariance function estimates.
CXCOV(a,b), where a and b represent samples taken over time interval T, which is assumed to be a common period of two corresponding periodic signals.

a and b are supposed to be length M row vectors, either real or complex.

[x,c]=CXCOV(a,b) returns the length M-1 circular cross covariance sequence c with corresponding lags x.

The circular cross covariance is the normalized circular cross correlation function of two vectors with their means removed:
c(k) = sum[a(n)-mean(a))*conj(b(n+k)-mean(b))]/[norm(a-mean(a))*norm(b-mean(b))];
where vector b is shifted CIRCULARLY by k samples.

The function doesn't check the format of input vectors a and b!

For circular correlation between a and b look for CXCORR(a,b) in

A. V. Oppenheim, R. W. Schafer and J. R. Buck, Discrete-Time Signal Processing, Upper Saddler River, NJ : Prentice Hall, 1999.

Author: G. Levin, April 2004.

Cite As

G. Levin (2023). Circular Cross Covariance (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R13
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired: Fast Circular Cross Covariance

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes

Misspell correction.
Add help.
Minor change in link.